Techniques for hybrid behavioral pairing in a contact center system

ABSTRACT

Techniques for hybrid behavioral pairing in a contact center system are disclosed. In one embodiment, the techniques may be realized as a method for hybrid behavioral pairing in a contact center system comprising: determining a first ordering of a plurality of contacts according to a behavioral pairing strategy with a balanced contact utilization; determining a second ordering of the plurality of contacts according to a performance-based routing strategy with an unbalanced contact utilization; determining a third ordering of the plurality of agents according to a combination of the first ordering and the second ordering having a skewed contact utilization between the balanced contact utilization and the unbalanced contact utilization; and outputting a hybrid behavioral pairing model based on the third ordering for connecting an agent to a contact of the plurality of contacts in the contact center system.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/444,972, filed Jun. 18, 2019, now U.S. Pat. No. 10,750,023, which isa continuation of U.S. patent application Ser. No. 15/686,945, filedAug. 25, 2017, now U.S. Pat. No. 10,326,884, issued Jun. 18, 2019, whichis a continuation of U.S. patent application Ser. No. 14/956,074, filedDec. 1, 2015, now U.S. Pat. No. 9,787,841, issued Oct. 10, 2017, whichis a continuation-in-part of U.S. patent application Ser. No.14/871,658, filed Sep. 30, 2015, now U.S. Pat. No. 9,300,802, issuedMar. 29, 2016, which is a continuation-in-part of U.S. patentapplication Ser. No. 12/021,251, filed Jan. 28, 2008, now U.S. Pat. No.9,712,679, issued Jul. 18, 2017, and is a continuation-in-part of U.S.patent application Ser. No. 14/530,058, filed Oct. 31, 2014, now U.S.Pat. No. 9,277,055, issued Mar. 1, 2016, which is a continuation of U.S.patent application Ser. No. 13/843,724, filed Mar. 15, 2013, now U.S.Pat. No. 8,879,715, issued Nov. 4, 2014, which claims priority to U.S.Provisional Patent Application No. 61/615,788, filed Mar. 26, 2012, U.S.Provisional Patent Application No. 61/615,779, filed Mar. 26, 2012, andU.S. Provisional Patent Application No. 61/615,772, filed Mar. 26, 2012,each of which is hereby incorporated by reference in their entirety asif fully set forth herein.

This application is also related to U.S. patent application Ser. No.14/956,086, entitled “Techniques for Hybrid Behavioral Pairing in aContact Center System,” filed Dec. 1, 2015, and U.S. patent applicationSer. No. 15/687,000, entitled “Techniques for Hybrid Behavioral Pairingin a Contact Center System,” filed Aug. 25, 2017.

FIELD OF THE DISCLOSURE

This disclosure generally relates to contact centers and, moreparticularly, to techniques for hybrid behavioral pairing in a contactcenter system.

BACKGROUND OF THE DISCLOSURE

A typical contact center algorithmically assigns contacts arriving atthe contact center to agents available to handle those contacts. Attimes, the contact center may have agents available and waiting forassignment to inbound or outbound contacts (e.g., telephone calls,Internet chat sessions, email) or outbound contacts. At other times, thecontact center may have contacts waiting in one or more queues for anagent to become available for assignment.

In some typical contact centers, contacts are assigned to agents orderedbased on time of arrival. This strategy may be referred to as a“first-in, first-out”, “FIFO”, or “round-robin” strategy. In somecontact centers, contacts or agents are assigned into different “skillgroups” or “queues” prior to applying a FIFO assignment strategy withineach such skill group or queue. These “skill queues” may alsoincorporate strategies for prioritizing individual contacts or agentswithin a baseline FIFO ordering. For example, a high-priority contactmay be given a queue position ahead of other contacts who arrived at anearlier time, or a high-performing agent may be ordered ahead of otheragents who have been waiting longer for their next call. Regardless ofsuch variations in forming one or more queues of callers or one or moreorderings of available agents, contact centers typically apply FIFO tothe queues or other orderings. Once such a FIFO strategy has beenestablished, assignment of contacts to agents is automatic, with thecontact center assigning the first contact in the ordering to the nextavailable agent, or assigning the first agent in the ordering to thenext arriving contact. In the contact center industry, the process ofcontact and agent distribution among skill queues, prioritization andordering within skill queues, and subsequent FIFO assignment of contactsto agents is managed by a system referred to as an “Automatic CallDistributor” (“ACD”).

Some contact centers may use a “priority queuing” or “PQ” approach toordering the queue of waiting contacts. For example, the ordering ofcontacts waiting for assignment to an agent would be headed by thehighest-priority waiting contact (e.g., the waiting contact of a typethat contributes to the highest sales conversion rate, the highestcustomer satisfaction scores, the shortest average handle time, thehighest performing agent for the particular contact profile, the highestcustomer retention rate, the lowest customer retention cost, the highestrate of first-call resolution). PQ ordering strategies attempt tomaximize the expected outcome of each contact-agent interaction but doso typically without regard for utilizing contacts in a contact centeruniformly. Consequently, lower-priority contacts may experiencenoticeably longer waiting times.

In view of the foregoing, it may be understood that there is a need fora system that both attempts to utilize agents more evenly than PQ whileimproving contact center performance beyond what FIFO strategiesdeliver.

SUMMARY OF THE DISCLOSURE

Techniques for hybrid behavioral pairing in a contact center system aredisclosed. In one embodiment, the techniques may be realized as a methodfor hybrid behavioral pairing in a contact center system comprising:determining, by at least one computer processor communicatively coupledto the contact center system, a first ordering of a plurality ofcontacts according to a behavioral pairing strategy with a balancedcontact utilization; determining, by the at least one computerprocessor, a second ordering of the plurality of contacts according to aperformance-based routing strategy with an unbalanced contactutilization; determining, by the at least one computer processor, athird ordering of the plurality of agents according to a combination ofthe first ordering and the second ordering having a skewed contactutilization between the balanced contact utilization and the unbalancedcontact utilization; and outputting, by the at least one computerprocessor, a hybrid behavioral pairing model based on the third orderingfor connecting an agent to a contact of the plurality of contacts in thecontact center system.

In accordance with other aspects of this embodiment, the behavioralpairing strategy may be a diagonal pairing strategy.

In accordance with other aspects of this embodiment, the method mayfurther comprise determining, by the at least one computer processor, atarget amount of skew for the skewed contact utilization.

In accordance with other aspects of this embodiment, the combination ofthe first ordering and the second ordering may be a weighted sumaccording to the target amount of skew.

In accordance with other aspects of this embodiment, the first orderingmay be expressed as percentiles or percentile ranges.

In accordance with other aspects of this embodiment, the third orderingmay be expressed as percentiles or percentile ranges adjusted accordingto the combination of the first ordering and the second ordering.

In accordance with other aspects of this embodiment, the hybridbehavioral pairing model preferably pairs a higher-priority contact morefrequently than a lower-priority agent.

In accordance with other aspects of this embodiment, the hybridbehavioral pairing model preferably pairs a higher-priority contact witha greater number of agents than a lower-priority contact.

In another embodiment, the techniques may be realized as a system forhybrid behavioral pairing in a contact center system comprising at leastone computer processor communicatively coupled to the contact centersystem, wherein the at least one computer processor is configured to:determine a first ordering of a plurality of contacts according to abehavioral pairing strategy with a balanced contact utilization;determine a second ordering of the plurality of contacts according to aperformance-based routing strategy with an unbalanced contactutilization; determine a third ordering of the plurality of agentsaccording to a combination of the first ordering and the second orderinghaving a skewed contact utilization between the balanced contactutilization and the unbalanced contact utilization; and output a hybridbehavioral pairing model based on the third ordering for connecting anagent to a contact of the plurality of contacts in the contact centersystem.

In another embodiment, the techniques may be realized as an article ofmanufacture for hybrid behavioral pairing in a contact center systemcomprising a non-transitory processor readable medium and instructionsstored on the medium, wherein the instructions are configured to bereadable from the medium by at least one computer processorcommunicatively coupled to the contact center system and thereby causethe at least one computer processor to operate so as to: determine afirst ordering of a plurality of contacts according to a behavioralpairing strategy with a balanced contact utilization; determine a secondordering of the plurality of contacts according to a performance-basedrouting strategy with an unbalanced contact utilization; determine athird ordering of the plurality of agents according to a combination ofthe first ordering and the second ordering having a skewed contactutilization between the balanced contact utilization and the unbalancedcontact utilization; and output a hybrid behavioral pairing model basedon the third ordering for connecting an agent to a contact of theplurality of contacts in the contact center system.

The present disclosure will now be described in more detail withreference to particular embodiments thereof as shown in the accompanyingdrawings. While the present disclosure is described below with referenceto particular embodiments, it should be understood that the presentdisclosure is not limited thereto. Those of ordinary skill in the arthaving access to the teachings herein will recognize additionalimplementations, modifications, and embodiments, as well as other fieldsof use, which are within the scope of the present disclosure asdescribed herein, and with respect to which the present disclosure maybe of significant utility.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to facilitate a fuller understanding of the present disclosure,reference is now made to the accompanying drawings, in which likeelements are referenced with like numerals. These drawings should not beconstrued as limiting the present disclosure, but are intended to beillustrative only.

FIG. 1 shows a block diagram of a contact center according toembodiments of the present disclosure.

FIG. 2 shows a schematic representation of a queue according toembodiments of the present disclosure.

FIG. 3 shows a schematic representation of a queue according toembodiments of the present disclosure.

FIG. 4 shows a schematic representation of a queue according toembodiments of the present disclosure.

FIG. 5 shows a schematic representation of a queue according toembodiments of the present disclosure.

FIG. 6 shows a schematic representation of a queue according toembodiments of the present disclosure.

FIG. 7 shows a schematic representation of a queue according toembodiments of the present disclosure.

FIG. 8 shows a flow diagram of a hybrid behavioral pairing methodaccording to embodiments of the present disclosure.

DETAILED DESCRIPTION

A typical contact center algorithmically assigns contacts arriving atthe contact center to agents available to handle those contacts. Attimes, the contact center may be in an “L1 state” and have agentsavailable and waiting for assignment to inbound or outbound contacts(e.g., telephone calls, Internet chat sessions, email). At other times,the contact center may be in an “L2 state” and have contacts waiting inone or more queues for an agent to become available for assignment. SuchL2 queues could be inbound, outbound, or virtual queues. Contact centersystems implement various strategies for assigning contacts to agents inboth L1 and L2 states.

The present disclosure generally relates to contact center systems,traditionally referred to as “Automated Call Distribution” (“ACD”)systems. Typically, such an ACD process is subsequent to an initial“Skills-based Routing” (“SBR”) process that serves to allocate contactsand agents among skill queues within the contact center. Such skillqueues may distinguish contacts and agents based on languagecapabilities, customer needs, or agent proficiency at a particular setof tasks.

The most common traditional assignment method within a queue is“First-In, First-Out” or “FIFO” assignment wherein the longest-waitingcontact is assigned to the longest-waiting agent. Some contact centersimplement “priority queuing” (“PQ”) wherein the next available agent isassigned to the highest-priority contact. Variations of both suchassignment methods commonly exist.

Variations of FIFO typically target “fairness” inasmuch as they aredesigned to balance the allocation (“utilization”) of contacts to agentsover time. PQ variations of FIFO adopt a different approach in which theallocation of contacts to agents is purposefully skewed to increase theutilization of higher-priority contacts and reduce the utilization oflower-priority contacts. PQ may do so despite potential negative impactson lower-priority contacts.

The present disclosure refers to optimized strategies for assigningcontacts to agents that improve upon traditional assignment methods,such as “Behavioral Pairing” or “BP” strategies. Behavioral Pairingtargets balanced utilization of both agents and contacts within queues(e.g., skill queues) while simultaneously improving overall contactcenter performance potentially beyond what FIFO or similar methods willachieve in practice. This is a remarkable achievement inasmuch as BPacts on the same contacts and same agents as FIFO, approximatelybalancing the utilization of contacts as FIFO provides, while improvingoverall contact center performance beyond what FIFO provides inpractice.

BP improves performance by assigning agent and contact pairs in afashion that takes into consideration the assignment of potentialsubsequent agent and contact pairs such that when the benefits of allassignments are aggregated they may exceed those of FIFO and PQstrategies. In some cases, BP results in instant contact and agentpairings that may be the reverse of what FIFO or PQ would indicate. Forexample, in an instant case BP might select the shortest-waiting contactor the lowest-performing available agent. BP respects “posterity”inasmuch as the system allocates contacts to agents in a fashion thatinherently forgoes what may be the highest-performing selection at theinstant moment if such a decision increases the probability of bettercontact center performance over time.

As explained in detail below, embodiments of the present disclosurerelate to techniques for “hybrid behavioral pairing” (“HBP”), whichcombines strategies of BP with strategies of priority queuing, in amanner in which a contact center administrator may adjust a balancebetween the two. For example, a contact center administrator may chooseto have BP be the dominant mechanism for assigning contacts from withina queue with a bias toward PQ. Instead of targeting a balanced contactutilization, HBP may target a skewed contact utilization. In someconfigurations, this bias or skew may be slight; for example, an HBPstrategy may be calibrated to reduce or limit the number of occasions inwhich any one type of contact in a queue (e.g., skill queue) is assignedto more than one agent pairing before other types of contacts in thequeue.

FIG. 1 shows a block diagram of a contact center system 100 according toembodiments of the present disclosure. The description herein describesnetwork elements, computers, and/or components of a system and methodfor simulating contact center systems that may include one or moremodules. As used herein, the term “module” may be understood to refer tocomputing software, firmware, hardware, and/or various combinationsthereof. Modules, however, are not to be interpreted as software whichis not implemented on hardware, firmware, or recorded on a processorreadable recordable storage medium (i.e., modules are not software perse). It is noted that the modules are exemplary. The modules may becombined, integrated, separated, and/or duplicated to support variousapplications. Also, a function described herein as being performed at aparticular module may be performed at one or more other modules and/orby one or more other devices instead of or in addition to the functionperformed at the particular module. Further, the modules may beimplemented across multiple devices and/or other components local orremote to one another. Additionally, the modules may be moved from onedevice and added to another device, and/or may be included in bothdevices.

As shown in FIG. 1, the contact center system may include a centralswitch 110. The central switch 110 may receive incoming contacts (e.g.,callers) or support outbound connections to contacts via a dialer, atelecommunications network, or other modules (not shown). The centralswitch 110 may include contact routing hardware and software for helpingto route contacts among one or more contact centers, or to one or morePBX/ACDs or other queuing or switching components within a contactcenter.

The central switch 110 may not be necessary if there is only one contactcenter, or if there is only one PBX/ACD routing component, in thecontact center system 100. If more than one contact center is part ofthe contact center system 100, each contact center may include at leastone contact center switch (e.g., contact center switches 120A and 120B).The contact center switches 120A and 120B may be communicatively coupledto the central switch 110.

Each contact center switch for each contact center may becommunicatively coupled to a plurality (or “pool”) of agents. Eachcontact center switch may support a certain number of agents (or“seats”) to be logged in at one time. At any given time, a logged-inagent may be available and waiting to be connected to a contact, or thelogged-in agent may be unavailable for any of a number of reasons, suchas being connected to another contact, performing certain post-callfunctions such as logging information about the call, or taking a break.

In the example of FIG. 1, the central switch 110 routes contacts to oneof two contact centers via contact center switch 120A and contact centerswitch 120B, respectively. Each of the contact center switches 120A and120B are shown with two agents each. Agents 130A and 130B may be loggedinto contact center switch 120A, and agents 130C and 130D may be loggedinto contact center switch 120B.

The contact center system 100 may also be communicatively coupled to anintegrated service from, for example, a third party vendor. In theexample of FIG. 1, hybrid behavioral pairing module 140 may becommunicatively coupled to one or more switches in the switch system ofthe contact center system 100, such as central switch 110, contactcenter switch 120A, or contact center switch 120B. In some embodiments,switches of the contact center system 100 may be communicatively coupledto multiple hybrid behavioral pairing modules. In some embodiments,hybrid behavioral pairing module 140 may be embedded within a componentof a contact center system (e.g., embedded in or otherwise integratedwith a switch).

The hybrid behavioral pairing module 140 may receive information from aswitch (e.g., contact center switch 120A) about agents logged into theswitch (e.g., agents 130A and 130B) and about incoming contacts viaanother switch (e.g., central switch 110) or, in some embodiments, froma network (e.g., the Internet or a telecommunications network) (notshown).

The hybrid behavioral pairing module 140 may process this informationand to determine which contacts should be paired (e.g., matched,assigned, distributed, routed) with which agents. For example, multipleagents are available and waiting for connection to a contact (L1 state),and a contact arrives at the contact center via a network or centralswitch. As explained below, without the hybrid behavioral pairing module140 or similar behavioral pairing module, a contact center switch willtypically automatically distribute the new contact to whicheveravailable agent has been waiting the longest amount of time for an agentunder a “fair” FIFO strategy, or whichever available agent has beendetermined to be the highest-performing agent under another strategysuch as a performance-based routing (“PBR”) strategy.

With the hybrid behavioral pairing module 140 or a similar behavioralpairing module, contacts and agents may be given scores (e.g.,percentiles or percentile ranges/bandwidths) according to a pairingmodel or other artificial intelligence data model, so that a contact maybe matched, paired, or otherwise connected to a preferred agent. In someembodiments, the hybrid behavioral pairing module 140 may be configuredwith an HBP strategy that blends the BP and PBR strategies, targetingbiased rather than balanced agent utilization.

In an L2 state, multiple contacts are available and waiting forconnection to an agent, and an agent becomes available. These contactsmay be queued in a contact center switch such as a PBX or ACD device(“PBX/ACD”). Without the hybrid behavioral pairing module 140 or asimilar behavioral pairing module, a contact center switch willtypically connect the newly available agent to whichever contact hasbeen waiting on hold in the queue for the longest amount of time as in a“fair” FIFO strategy or a PBR strategy when agent choice is notavailable. In some contact centers, priority queuing may also beincorporated.

With the hybrid behavioral pairing module 140 or similar behavioralpairing module in an L2 scenario, as in the L1 state described above,contacts and agents may be given percentiles (or percentileranges/bandwidths, etc.) according to, for example, a model, such as another artificial intelligence model, so that an agent coming availablemay be matched, paired, or otherwise connected to a preferred contact.

Under an HBP strategy, a hybridization factor or function may be appliedto one or more orderings of agents to achieve the desired balancebetween a BP strategy, which targets a balanced utilization, and a PQstrategy, which targets a highly skewed utilization during periods oftime when a contact center is in an L2 state (i.e., multiple contactswaiting for assignment).

In some embodiments, a hybridization function may combine two (or more)orderings or other types of ranking systems together. For example, acontact center may have four contacts of different types: Contact A,Contact B, Contact C, and Contact D (“A”, “B”, “C”, and “D”) availablefor pairing with an agent. The contacts may be ordered according tomultiple ordering systems. For example, under a typical FIFO strategy,the agents may be ordered according to how long each contact has beenwaiting for an assignment relative to the other contacts. Under atypical priority queuing strategy, the contacts may be ordered accordingto how well each contact contributes to performance for some metricrelative to the other contacts. Under a BP strategy, the agents may beordered according to the quality of each agent's “behavioral fit”relative to the other agents.

One technique for combining two orderings is to determine a sum. Forexample, if a PQ strategy orders the four contacts as A=1, B=2, C=3, andD=4, the PQ strategy would preferably pair highest-“performing” ContactA with the next agent. And if a BP strategy order the contacts as A=4,B=2, C=3, D=1, the BP strategy would preferably pair best-fittingContact D with the next agent. In this example of an HBP strategy, thesum of the two orderings would be A=5, B=4, C=6, D=5. This HBP strategywould preferably pair Contact B with the next agent, which is the secondhighest-performing and second best-fitting agent according to theoriginal orderings.

Other embodiments may use other techniques for combining multipleorderings of agents. For example, the HBP ordering may be a productobtained by multiplying two or more orderings. For another example, theHBP ordering may be a weighted sum or product obtained by scaling theone or more of the orderings by a scaling factor. In this way, HBP maybe configured to weight an agent's relative performance more or lessthan the agent's relative behavioral fit.

FIG. 2 shows a queue 200 according to embodiments of the presentdisclosure operating under BP Strategy 210. Queue 200 represents asimplified hypothetical case in which four types of contacts may beassigned to any of four agents in an environment in which the contactcenter is seeking to maximize a desired metric (e.g., sales). The fourevenly distributed types of contacts are assigned percentile ranges (or“bandwidths”) of 0.00 to 0.25 (“0-25% Contacts”), 0.25 to 0.50 (“25-50%Contacts”), 0.50 to 0.75 (“50-75% Contacts”), and 0.75 to 1.00 (75-100%Contacts). The four agents occupy equally-spaced percentile bandwidthsand are assigned percentiles at the midpoints of their respectiveranges: 0.00 to 0.25 (“0.125 Agent”), 0.25 to 0.50 (“0.375 Agent”), 0.50to 0.75 (“0.625 Agent”), and 0.75 to 1.00 (“0.875 Agent”). The fouragents may also be ordered by performance according to a desired metric(e.g., sales), such that the lowest-performing agent is assigned thelowest percentile (the 0.125 Agent), and the highest-performing agent isassigned the highest percentile (the 0.875 Agent).

By applying a diagonal strategy, 0-25% Contacts may be preferablyassigned to the 0.125 Agent, 25-50% Contacts may be preferably assignedto the 0.375 Agent, 50-75% Contacts may be preferably assigned to the0.625 Agent, and 75-100% Contacts may be preferably assigned to the0.875 Agent. BP Strategy 210 targets a balanced utilization, with eachagent receiving approximately the same proportion of contacts over time.Accordingly, there is no bias toward a PQ strategy, under which contactutilization would be skewed toward utilizing the highest-performing75-100% Contacts more heavily.

One such technique for generating the performance-biased contact typepercentiles according to embodiments of the present disclosure is toadjust each contact type's “initial” midpoint percentile(“CP_(initial)”) by a hybridization function or factor, such thatrelatively higher-ordered (e.g., higher-performing) contacts occupyrelatively larger bandwidths and, consequently, receive relatively morecontacts than lower-ordered (e.g., lower-performing) contacts. Forexample, the hybridization function may raise each contact's percentileto a power, as in Equation 1 below:CP _(adjusted) =CP _(initial) ^(ρ)  (Eqn. 1)The power parameter (e.g., “ρ” or a “Rho parameter” as in Equation 1 maydetermine the amount of bias toward PQ, with higher values of Rhogenerating greater amounts of bias. A Rho parameter of 1.0 wouldgenerate no bias (CP_(adjusted)=CP_(initial)). Thus, this “neutral”value for Rho results in targeting a balanced contact utilization. Infact, BP Strategy 210 is equivalent to a Rho-based HBP strategy in whichRho equals 1.0. As Rho increases, the degree of contact utilization skewincreases as bias toward PQ increases.

FIG. 3 shows a queue 300 that applies this technique using a Rho valueof 2.0. Queue 300 represents the same four types of contacts and thesame four agents as in queue 200. However, in queue 300, the contacttypes' percentile midpoints have been squared(CP_(adjusted)=CP_(initial) ^(2.0)). Applying a diagonal strategy underHBP Strategy 310, the lowest-ordered contact type (CP_(adjusted)≈0.016)would occupy the smallest bandwidth and be selected least frequently,and so on, up to the highest-ordered contact type (CP_(adjusted)≈0.766),which would occupy the largest bandwidth and be selected mostfrequently.

In some embodiments, the bandwidth of each contact type may bedetermined so that each contact type's adjusted percentile midpoint isthe midpoint of each contact type's new, adjusted bandwidth. Forexample, the bandwidth of the lowest-ordered 0.016 contact type may beapproximately 0.000 to 0.031 In other embodiments, the bandwidth of eachagent may be determined by equally distributing the “distance” betweenneighboring adjusted percentile midpoints. For example, the bandwidth ofthe lowest-ordered 0.016 contact type may be approximately 0.000 to0.079.

Another variation of the HBP technique applied to queue 300 in FIG. 3 isto adjust each contact type's initial percentile ranges rather than eachcontact type's initial midpoint percentile, as in Equation 2 below:CP _(adjusted_range) =CP _(initial_range) ^(ρ)  (Eqn. 2)The effect would be the same: relatively higher-ordered (e.g., highervalue) contact types occupy relatively larger bandwidths and,consequently, are selected relatively more frequently than lower-ordered(e.g., lower value) contact types.

FIG. 4 shows a queue 400 that applies this technique using a Rho valueof 2.0. Queue 400 represents the same four contact types and agents asin queue 300. However, in queue 400, the contact types' initialpercentile ranges have been squared(CP_(adjusted_range)=CP_(initial_range) ^(2.0)) instead of their initialmidpoint percentiles. Applying a diagonal strategy under HBP Strategy410, the lowest-ordered contact type (occupying adjusted percentilerange from 0.00 to approximately 0.06 with a midpoint of approximately0.03) would be selected least frequently, and so on, up to thehighest-ordered contact type (occupying adjusted percentile range fromapproximately 0.56 to 1.00 with a midpoint of approximately 0.82), whichwould be selected most frequently.

Conceptually, the target skewed utilization would result in thehighest-ordered contact type being selected a little less than half ofthe time, typically when one of the top-half of agents becomesavailable, and the lower-ordered contact types being selected a littlemore than half of the time, typically when one of the bottom-half ofagents becomes available. Other techniques for visualizing orimplementing these hybridization functions or factors include adjustingthe “fitting function” of the diagonal strategy.

FIG. 5 shows a queue 500 with the same contact type percentiles andranges as in queue 100 (FIG. 1), and they have not been adjusted. Unlikequeue 100, in which BP Strategy 110 may be visualized by a 45-degreediagonal line (CP=AP), HBP strategy 510 may be visualized by adifferent, hybridized fitting function (e.g., “bending” or “bowing” thediagonal line). In the example, of FIG. 5, the fitting function is anexponential function, as in Equation 3 below:AP=CP ^(ρ)  (Eqn. 3)Conceptually, instead of determining preferred pairings by selectingpairs closest to the diagonal AP=CP as in BP Strategy 110, preferredpairings in HBP Strategy 510 may be determined by selecting pairsclosest to the exponential AP=CP^(2.0) as in queue 500 where Rho equals2.0. Notably, the effect of fitting to AP=CP^(2.0) is the continuousmathematical analogue to the discontinuous process of broadening orshrinking percentile ranges (e.g., squaring the percentile ranges andthen fitting to AP=CP, as in queue 400 and HBP Strategy 410 (FIG. 4).

Many variations of hybridization functions may be used to vary thetarget utilization of an agent as a function of the agent's performanceor other ordering or metric. For example, a hybridization function maybe a piecewise function.

FIG. 6 shows a queue 600 and HBP Strategy 610 that affects theutilization of the bottom-half of the contact types differently thanthat of the top-half of the contact types. For example, the contactcenter may determine that half of the contacts should be distributed tobelow-average agents in a balanced manner (e.g., Rho=1.0), but the otherhalf of the contacts should be distributed to above-average agentsaccording to each contact type's relative ordering (e.g., Rho>1.0).Thus, contacts ranging from 0% to 50% may be distributed to thelower-performing agents (0.125 Agent and 0.375 Agent) evenly, visualizedas a fit along the 45-degree line AP=CP for 0.00≤CP<0.50 (or, e.g.,0.00<CP≤0.50, etc.). Contacts ranging from 50% to 100% may bedistributed to the higher-performing agents (0.625 Agent and 0.875Agent) as a function of their contact type's relative ordering (e.g.,value), such as an exponential function scaled to this portion ofcontacts and agents. HBP Strategy 610 may be visualized as a fit alongthe exponential curve AP=2(CP-0.5)^(2.0)+0.5 for Rho=2.0 and0.50≤CP<1.00.

Incidentally, such a strategy would result in some higher-orderedcontact types (here, the 0.50 to 0.75 contact type) being selected lessfrequently over time than its lower-ordered peers. FIG. 7 shows a queue700 and HBP Strategy 710 that also affects the utilization of thebottom-half of the contacts differently than that of the top-half of thecontacts using a piecewise hybridization function. For example, thecontact center may determine that a larger portion of contacts should bedistributed to above-average agents according to their relative ordering(e.g., Rho>1.0), and the remaining portion of contacts should bedistributed to below-average agents in a balanced manner (e.g.,Rho=1.0). Thus, for Rho=2.0 and CP≥0.50 (or CP>0.50), pairings may befit along the exponential curve AP=CP^(2.0). For Rho=1.0 and CP<0.50,pairings may be fit along a linear function, scaled to this portion ofcontacts and agents: AP=0.5·CP.

In real-world contact centers, there may be more or fewer agents, andmore or fewer contact types in a queue. In these examples, each contacttype is evenly distributed within the total range of percentile ranks;however, in some contact centers, the distribution of ranges could varybased on, for example, the frequency at which contacts of a particulartype arrive at a contact center relative to the frequency at whichcontacts of other types arrive. The simplified examples described above,with four agents and four contact types, are used to illustrate theeffects of an implicit form of HBP such as those based on a Rhoparameter and exponential scaling or other hybridization functions.However, HBP—including Rho-based techniques—may also be applied tobigger, more complex, real-world contact centers.

In some embodiments, Rho may be selected or adjusted to vary the biastoward PQ (or skew in contact utilization). For example, Rho less than2.0 (e.g., 1.0, 1.01, 1.1, 1.2, 1.5, etc.) would result in relativelyless bias toward PQ than the examples above in which Rho equals 2.0. Forexample, if a contact center administrator wanted to avoid occurrencesof higher-ordered contact types being selected multiple times while alower-ordered contact type remains unselected, a significantly lowervalue of Rho may be more appropriate than 2.0. Conversely, Rho greaterthan 2.0 (e.g., 2.01, 2.1, 2.5, 200.0, etc.) would result in relativelymore bias toward PQ.

Importantly, the effect on contact utilization is subtle under Rho-basedHBP strategies inasmuch as they controllably affect the degree to whichcontacts of differently ordered contact types wait for connection to anagent. By increasing the power to which contact percentiles are raised,this invention controllably decreases the average time betweenselections for higher-ordered contact types and increases the averagetime between selections for comparatively lower-ordered contact types.Similarly, reducing the power to which contact percentiles are raisedhas the reverse effect. For neutral BP strategies (e.g., Rho=1.0), eachagent has approximately the same expected average waiting time betweencontacts. As Rho increases, the relative expected average waiting timeprogressively (e.g., exponentially) decreases as relative contact typeordering (e.g., contact type value) increases.

In some embodiments, an HBP strategy may target relative contactutilization using potentially more gradual techniques. For example,contact types may be assigned relative “utilization adjustments” basedon contact type ordering. In one example, the highest-ordered contacttype may be assigned a relative utilization adjustment of 100%, thesecond-highest contact type a relative utilization of 99%, the third98%, and so on. In this example, the target utilization of thesecond-highest ordered contact type would be 99% of the targetutilization of the highest-ordered contact type. The relativeutilization adjustment may be more aggressive in other configurations.For example, the highest-ordered contact type may be assigned a relativeutilization of 100%, the second-highest contact type 90%, the third 80%,and so on. In this example, the target utilization of the second-highestordered contact type would be 90% of the target utilization of thehighest-ordered contact type.

FIG. 8 shows a hybrid behavioral pairing method 800 according toembodiments of the present disclosure. At block 810, hybrid behavioralpairing method 800 may begin.

At block 810, a percentile (or n-tile, quantile, percentile range,bandwidth, or other type of “score” or range of scores, etc.) may bedetermined for each available contact. For situations in which contactsare waiting on hold in a queue, percentiles may be determined for eachof the contacts waiting on hold in the queue. For situations in whichcontacts are not waiting on hold in a queue, a percentile may beassigned to the next contact to arrive at the contact center. Thepercentiles may be bounded by a range of percentiles defined for aparticular type or group of contacts based on information about thecontact. The percentile bounds or ranges may be based on a frequencydistribution or other metric for the contact types. The percentile maybe randomly assigned within the type's percentile range.

In some embodiments, percentiles may be ordered according to aparticular metric or combination of metrics to be optimized in thecontact center, and a contact determined to have a relatively highpercentile may be considered to be a “higher-value” contact for thecontact center inasmuch as these contacts are more likely to contributeto a higher overall performance in the contact center. For example, arelatively high-percentile contact may have a relatively high likelihoodof making a purchase.

In some embodiments, a percentile may be determined for a contact at thetime the contact arrives at the contact center. In other embodiments, apercentile may be determined for the contact at a later point in time,such as when the contact arrives at a particular skill queue or ACDsystem, or when a request for a pairing is made.

After a percentile has been determined for each contact available forpairing, behavioral pairing method 800 may proceed to block 820. In someembodiments, block 820 may be performed prior to, or simultaneouslywith, block 810.

At block 820, a percentile may be determined for each available agent.For situations in which agents are idle, waiting for contacts to arrive,percentiles may be determined for each of the idle agents. Forsituations in which agents for a queue are all busy, a percentile may bedetermined to the next agent to become available. The percentiles may bebounded by a range of percentiles (e.g., “bandwidth”) defined based onall of agents assigned to a queue (e.g., a skill queue) or only theavailable agents assigned to a particular queue. In some embodiments,the bounds or ranges of percentiles may be based on a desired agentutilization (e.g., for fairness, efficiency, or performance).

In some embodiments, agent percentiles may be ordered according to aparticular metric or combination of metrics to be optimized in thecontact center, and an agent determined to have a relatively highpercentile may be considered to be a higher-performing agent for thecontact center. For example, a relatively high-percentile agent may havea relatively high likelihood of making a sale.

In some embodiments, an agent's percentile may be determined at the timethe agent becomes available within the contact center. In otherembodiments, a percentile may be determined at a later point in time,such as when a request for a pairing is made.

After a percentile has been determined for each available agent andcontact, behavioral pairing method 800 may proceed to block 830.

At block 830, a hybridization function may be applied to contact typepercentiles (or contact type percentile ranges or bandwidths). Forexample, a Rho value may be determined for an exponential hybridizationfunction or fitting curve or line. In some embodiments, thehybridization function may act on a single ordering that implicitlyincorporates both behavioral fit and performance information. In otherembodiments, the hybridization function may combine (e.g., add,multiply, weight) multiple orderings of contact types. After thehybridization function has been applied or otherwise determined orconfigured, hybrid behavioral pairing method 800 may proceed to block840.

At block 840, a pair of an available contact and an available agent maybe determined based on the percentiles (or percentile ranges) determinedfor each available contact at block 810 and for each available agent atblock 820 based on a hybridization function. In some embodiments, theselection may be determined based on percentiles or percentile rangesfor each waiting contact or contact type adjusted at block 830. In someembodiments, the pair may be determined according to a diagonalstrategy, in which contacts and agents with more similar percentiles (orthe most similar percentiles) may be selected for pairing. For example,a hybrid behavioral pairing module may select a contact-agent pairingwith the smallest absolute difference between the contact's score andthe agent's score. In some embodiments, the diagonal strategy may bevisualized as a 45-degree diagonal line. In other embodiments, thediagonal strategy may be visualized as a hybridization function (e.g.,an exponential function, or a piecewise function).

In some situations, multiple agents may be idle when a contact arrives(an L1 state). Under HBP, the newly available contact may be paired witha selected one of the available agents that has a percentile orpercentile range more similar to the contact's adjusted percentile thanother available agents. In other situations, multiple contacts may bewaiting in a queue when an agent becomes available (an L2 state). UnderHBP, the newly available agent may be paired with a selected one of thecontacts waiting in the queue that has an adjusted percentile moresimilar to the agent's percentile or percentile range than othercontacts waiting in the queue.

In some situations, selecting a pairing based on similarity of scoresmay result in selecting an instant pairing that might not be the highestperforming instant pairing, but rather increases the likelihood ofbetter future pairings.

After a pairing has been determined at block 840, hybrid behavioralpairing method 800 may proceed to block 850. At block 850, moduleswithin the contact center system may cause the contact and agent of thecontact-agent pair to be connected with one another. For example, abehavioral pairing module may indicate that an ACD system or otherrouting device may distribute a particular contact to a particularagent.

After connecting the contact and agent at block 850, behavioral pairingmethod 800 may end. In some embodiments, behavioral pairing method 800may return to block 840 for determining one or more additional pairings(not shown). In other embodiments, behavioral pairing method 800 mayreturn to block 810 or block 820 to determine (or re-determine)percentiles or percentile ranges for available contacts or agents (notshown), and subsequently apply (or reapply) a hybridization function atblock 840.

At this point it should be noted that hybrid behavioral pairing in acontact center system in accordance with the present disclosure asdescribed above may involve the processing of input data and thegeneration of output data to some extent. This input data processing andoutput data generation may be implemented in hardware or software. Forexample, specific electronic components may be employed in a behavioralpairing module or similar or related circuitry for implementing thefunctions associated with behavioral pairing in a contact center systemin accordance with the present disclosure as described above.Alternatively, one or more processors operating in accordance withinstructions may implement the functions associated with behavioralpairing in a contact center system in accordance with the presentdisclosure as described above. If such is the case, it is within thescope of the present disclosure that such instructions may be stored onone or more non-transitory processor readable storage media (e.g., amagnetic disk or other storage medium), or transmitted to one or moreprocessors via one or more signals embodied in one or more carrierwaves.

The present disclosure is not to be limited in scope by the specificembodiments described herein. Indeed, other various embodiments of andmodifications to the present disclosure, in addition to those describedherein, will be apparent to those of ordinary skill in the art from theforegoing description and accompanying drawings. Thus, such otherembodiments and modifications are intended to fall within the scope ofthe present disclosure. Further, although the present disclosure hasbeen described herein in the context of at least one particularimplementation in at least one particular environment for at least oneparticular purpose, those of ordinary skill in the art will recognizethat its usefulness is not limited thereto and that the presentdisclosure may be beneficially implemented in any number of environmentsfor any number of purposes. Accordingly, the claims set forth belowshould be construed in view of the full breadth and spirit of thepresent disclosure as described herein.

The invention claimed is:
 1. A method for behavioral pairing in acontact center system comprising: ordering, by at least one computerprocessor communicatively coupled to and configured to performbehavioral pairing operations in the contact center system, a pluralityof agents available for connection to a contact according to arespective value or range of values representing how each agent of theplurality of agents contributes to a higher performance of the contactcenter system; ordering, by the at least one computer processor, aplurality of contacts available for connection to an agent according toat least one performance metric to be optimized in the contact centersystem; applying, by the at least one computer processor, ahybridization function to the ordering of the plurality of contacts tobias a contact-agent pairing strategy toward a skewed contact selection;selecting, by the at least one computer processor, a contact-agentpairing from the plurality of contacts and the plurality of agents basedat least in part on the biased contact-agent pairing strategy; andestablishing, by the at least one computer processor, in a switch of thecontact center system, a connection between the contact and the agent inthe contact-agent pairing based upon the selecting.
 2. The method ofclaim 1, wherein the ordering of the plurality of agents comprisesdetermining, by the at least one computer processor, a bandwidth foreach agent of the plurality of agents proportionate to a relativeperformance of the respective agent.
 3. The method of claim 1, whereinapplying the hybridization function comprises controllably targeting, bythe at least one computer processor, an unbalanced contact selection. 4.The method of claim 3, wherein applying the hybridization functioncomprises determining, by the at least one computer processor,disproportionate bandwidth for each of the plurality of contacts.
 5. Themethod of claim 1, wherein the selected contact-agent pairing results ina worse expected instant outcome than other non-selected contact-agentpairings.
 6. The method of claim 1, wherein each successivelyhigher-ordered contact of the plurality of contacts is more likely to beselected than respectively lower-ordered contacts.
 7. The method ofclaim 1, wherein each successively higher-ordered contact of theplurality of contacts is targeted to have a lower average waiting timethan respectively lower-ordered contacts.
 8. A system for behavioralpairing in a contact center system comprising: at least one computerprocessor communicatively coupled to and configured to performbehavioral pairing operations in the contact center system, wherein theat least one computer processor is configured to: order a plurality ofagents available for connection to a contact according to a respectivevalue or range of values representing how each agent of the plurality ofagents contributes to a higher performance of the contact center system;order a plurality of contacts available for connection to an agentaccording to at least one performance metric to be optimized in thecontact center system; apply a hybridization function to the ordering ofthe plurality of contacts to bias a contact-agent pairing strategytoward a skewed agent utilization; select a contact-agent pairing fromthe plurality of contacts and the plurality of agents based at least inpart on the biased contact-agent pairing strategy; and establish, in aswitch of the contact center system, a connection between the contactand the agent in the contact-agent pairing based upon the selecting. 9.The system of claim 8, wherein the ordering of the plurality of agentscomprises determining a bandwidth for each agent of the plurality ofagents proportionate to a relative performance of the respective agent.10. The system of claim 8, wherein applying the hybridization functioncomprises controllably targeting an unbalanced contact selection. 11.The system of claim 10, wherein applying the hybridization functioncomprises determining disproportionate bandwidth for each of theplurality of contacts.
 12. The system of claim 8, wherein the selectedcontact-agent pairing results in a worse expected instant outcome thanother non-selected contact-agent pairings.
 13. The system of claim 8,wherein each successively higher-ordered contact of the plurality ofcontacts is more likely to be selected than respectively lower-orderedcontacts.
 14. The system of claim 8, wherein each successivelyhigher-ordered contact of the plurality of contacts is targeted to havea lower average waiting time than respectively lower-ordered contacts.15. An article of manufacture for behavioral pairing in a contact centersystem comprising: a non-transitory processor readable medium; andinstructions stored on the medium; wherein the instructions areconfigured to be readable from the medium by at least one computerprocessor communicatively coupled to and configured to performbehavioral pairing operations in the contact center system and therebycause the at least one computer processor to operate so as to: order aplurality of agents available for connection to a contact according to arespective value or range of values representing how each agent of theplurality of agents contributes to a higher performance of the contactcenter system; order a plurality of contacts available for connection toan agent according to at least one performance metric to be optimized inthe contact center system; apply a hybridization function to theordering of the plurality of contacts to bias a contact-agent pairingstrategy toward a skewed agent utilization; select a contact-agentpairing from the plurality of contacts and the plurality of agents basedat least in part on the biased contact-agent pairing strategy; andestablish, in a switch of the contact center system, a connectionbetween the contact and the agent in the contact-agent pairing basedupon the selecting.
 16. The article of manufacture of claim 15, whereinthe ordering of the plurality of agents comprises determining abandwidth for each agent of the plurality of agents proportionate to arelative performance of the respective agent.
 17. The article ofmanufacture of claim 15, wherein applying the hybridization functioncomprises controllably targeting an unbalanced contact selection. 18.The article of manufacture of claim 15, wherein the selectedcontact-agent pairing results in a worse expected instant outcome thanother non-selected contact-agent pairings.
 19. The article ofmanufacture of claim 15, wherein each successively higher-orderedcontact of the plurality of contacts is more likely to be selected thanrespectively lower-ordered contacts.
 20. The article of manufacture ofclaim 15, wherein each successively higher-ordered contact of theplurality of contacts is targeted to have a lower average waiting timethan respectively lower-ordered contacts.